I am a PhD student in the Computer Science Department at the Johns Hopkins University. I am advised by René Vidal, and am affiliated with the Mathematical Institute for Data Science and the Vision Lab at JHU. Previously I obtained my Bachelor's degree in Computer Science from IIIT Delhi. My CV can be found here.
My current research interest lies in the theory of deep learning, specifically, trying to theoretically understand the properties induced by common deep learning techniques on the optimization of deep architectures. While deep learning has shown significant gains in performance on several computer vision tasks, the theoretical understanding of deep networks is quite shallow. I am currently working on understanding the regularization properties induced by common techniques used to prevent deep neural networks from overfitting. I have a secondary interest in understanding adversarial examples generated for computer vision systems.